Counter

Counter - Problem

JavaScript Easy

Given an integer n, return a counter function. This counter function initially returns n and then returns 1 more than the previous value every subsequent time it is called (n, n + 1, n + 2, etc).

The counter function should maintain its internal state between calls and increment the value each time it's invoked.

Input & Output

Example 1 — Positive Counter

$ Input: n = 10

› Output: [10, 11, 12]

💡 Note: counter() returns 10, then counter() returns 11, then counter() returns 12. Each call increments the internal state.

Example 2 — Negative Counter

$ Input: n = -2

› Output: [-2, -1, 0]

💡 Note: counter() returns -2, then counter() returns -1, then counter() returns 0. Works with negative starting values.

Example 3 — Zero Counter

$ Input: n = 0

› Output: [0, 1, 2]

💡 Note: counter() returns 0, then counter() returns 1, then counter() returns 2. Starting from zero and incrementing normally.

Constraints

-1000 ≤ n ≤ 1000
At most 1000 calls will be made to counter()

Visualization

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Asked in

G Google 15 f Meta 12 a Amazon 8

The key insight is using JavaScript closures to maintain state between function calls. The counter function captures the initial value n in its closure scope and uses the post-increment operator to return the current value while incrementing for the next call. Best approach uses arrow function syntax: (n) => () => n++. Time: O(1), Space: O(1)

Common Approaches

✓ Binary Search

⏱️ Time: N/A Space: N/A

Arrow Function Closure

⏱️ Time: O(1) Space: O(1)

A more modern JavaScript approach using arrow functions and the post-increment operator. This creates a cleaner, more concise implementation while maintaining the same closure behavior.

Basic Closure Implementation

⏱️ Time: O(1) Space: O(1)

Create a function that returns another function. The inner function has access to the outer function's variables (closure), allowing it to remember and modify the counter value between calls.

Algorithm Steps — Algorithm Steps

Code -

solution.c — C

Time & Space Complexity

Time Complexity

⏱️

✓ Linear Growth

Space Complexity

✓ Linear Space

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